Disentangling the relationships of health-related quality of life, depressive symptoms, disability and social support after stroke: A network analysis

Abstract

Background

Health-related quality of life (HRQOL), depressive symptoms, disability, and social support show complex interdependences after stroke, which cannot be sufficiently depicted by commonly used uni- or bivariate analyses. Applying a network analysis, we aim to disentangle these multivariate relationships and deduce meaningful starting points for interventions.

Methods

Stroke survivors (N = 202) were recruited from two inpatient rehabilitation clinics. Participants self-reported mental and physical HRQOL, depressive symptoms, disability, and social support. We computed a partial correlation network and included these five variables as separate nodes. We estimated edge weights, node centrality (expected influence), node predictability, and clusters. Bootstrap methods were applied to assess network stability.

Results

Depressive symptoms and mental HRQOL were the most central and interconnected nodes in the network. Depressive symptoms built its own cluster. Social support showed a high association with depressive symptoms. Disability had no significant associations with other nodes in the network. Physical HRQOL was significantly connected only to its mental equivalent.

Limitations

The cross-sectional design limits the findings to the setting of inpatient rehabilitation few weeks after stroke and allows no longitudinal inferences. The relatively small sample size and varying metrics of applied measures are counterbalanced by a high stability of estimations.

Conclusions

Depression and social support show stronger associations with HRQOL than physical aspects during stroke inpatient rehabilitation. This underscores the significance of mental aspects shortly after stroke. Development and implementation of early interventions targeting depressive symptoms and social support may sustainably mitigate the burden on HRQOL after stroke.